Wireless communication systems have become ubiquitous in society. Business and consumers use a wide variety of fixed and mobile wireless terminals, including cell phones, pagers, Personal Communication Services (PCS) systems, and fixed wireless access devices (i.e., vending machine with cellular capability). Wireless service providers continually try to create new markets for wireless devices and expand existing markets by making wireless devices and services cheaper and more reliable.
In code division multiple access (CDMA) networks, for example, adaptive antenna arrays have been developed to increase the capacity and quality of calls handled within CDMA networks. Adaptive antenna arrays use beam-forming techniques to provide directional antenna beams in the downlink from the base station to the wireless terminal. For example, angle of arrival (AOA) information determined from a received signal at an adaptive antenna array may be used to determine beam-forming coefficients that are used to generate a narrow beam spatially directed to a specific wireless terminal in the downlink (or forward channel). This provides improved capacity and signal quality. The narrow beam carries a traffic signal intended for the specific wireless terminal.
The prior art discloses a number of techniques for maximizing the throughput of a base transceiver station. Many of these techniques attempt to maximize throughput by selecting an optimum value of a particular variable, such as Walsh multiplexing (i.e., bits per Walsh code), or beam selection, or modulation rate. However, there are significant drawbacks to these conventional techniques. For instance, conventional CDMA base stations use a static table to look up the optimum discrete beamwidth for a specific location. The table is built during a specific learning or calibration phase. Once the table is built, the base station simply lookups the beamwidth for that location from the table.
However, using such a static table prevents the base station from compensating for changing conditions. The prior art systems either do not dynamically detect new beams or cannot detect optimum beams if the modulation scheme is modified. Also, the prior art techniques optimize the variables (i.e., Walsh multiplexing, modulation rate, beam selection) separately. Thus, the prior art techniques provide a local optimum value, but not a global optimum value.
Therefore, there is a need in the art for an improved downlink (or forward channel) beam-width optimizing system that is able to dynamically adapt to changing traffic conditions. In particular, there is a need for a base station that is capable of maximizing throughput by jointly optimizing more than one variable.